Browsing by Author "Wang, Ping"
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Item A Hierarchical Game With Strategy Evolution for Mobile Sponsored Content and Service Markets(IEEE Transactions on Communications, 9/24/2018) Wang, Wenbo; Xiong, Zehui; Niyato, Dusit; Wang, Ping; Han, ZhuIn sponsored content and service markets, the content and service providers are able to subsidize their target mobile users through directly paying the mobile network operator to lower the price of the data/service access charged by the network operator to the mobile users. The sponsoring mechanism leads to a surge in mobile data and service demand, which in return compensates for the sponsoring cost and benefits the content/service providers. In this paper, we study the interactions among the three parties in the market, namely, the mobile users, the content/service providers, and the network operator, as a two-level game with multiple Stackelberg (i.e., leader) players. Our study is featured by the consideration of global network effects owning to consumers' grouping. Since the mobile users may have bounded rationality, we model the service-selection process among them as an evolutionary-population follower sub-game. Meanwhile, we model the pricing-then-sponsoring process between the content/service providers and the network operator as a non-cooperative equilibrium searching problem. By investigating the structure of the proposed game, we reveal a few important properties regarding the equilibrium existence and propose a distributed, projection-based algorithm for iterative equilibrium searching. Simulation results validate the convergence of the proposed algorithm and demonstrate how sponsoring helps improve both the providers' profits and the users' experience.Item Applications of Economic and Pricing Models for Wireless Network Security: A Survey(IEEE Communications Surveys & Tutorials, 7/27/2017) Luong, Nguyen Cong; Hoang, Dinh Thai; Wang, Ping; Niyato, Dusit; Han, ZhuThis paper provides a comprehensive literature review on applications of economic and pricing theory to security issues in wireless networks. Unlike wireline networks, the broadcast nature and the highly dynamic change of network environments pose a number of nontrivial challenges to security design in wireless networks. While the security issues have not been completely solved by traditional or system-based solutions, economic and pricing models recently were employed as one efficient solution to discourage attackers and prevent attacks to be performed. In this paper, we review economic and pricing approaches proposed to address major security issues in wireless networks including eavesdropping attack, denial-of-service (DoS) attack such as jamming and distributed DoS, and illegitimate behaviors of malicious users. Additionally, we discuss integrating economic and pricing models with cryptography methods to reduce information privacy leakage as well as to guarantee the confidentiality and integrity of information in wireless networks. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to wireless security issues.Item Applications of Repeated Games in Wireless Networks: A Survey(IEEE Communications Surveys & Tutorials, 6/16/2015) Hoang, Dinh Thai; Lu, Xiao; Niyato, Dusit; Wang, Ping; Kim, Dong In; Han, ZhuA repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model interactions among players in only one period, in repeated games, interactions of players repeat for multiple periods. Thus, the players become aware of other players' past behaviors and their future benefits, so as to adapt their strategies accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games in encouraging wireless nodes into cooperations, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Item Cloud/Fog Computing Resource Management and Pricing for Blockchain Networks(IEEE Internet of Things Journal, 9/24/2018) Xiong, Zehui; Feng, Shaohan; Wang, Wenbo; Niyato, Dusit; Wang, Ping; Han, ZhuPublic blockchain networks using proof of work-based consensus protocols are considered a promising platform for decentralized resource management with financial incentive mechanisms. In order to maintain a secured, universal state of the blockchain, proof of work-based consensus protocols financially incentivize the nodes in the network to compete for the privilege of block generation through cryptographic puzzle solving. For rational consensus nodes, i.e., miners with limited local computational resources, offloading the computation load for proof of work to the cloud/fog providers becomes a viable option. In this paper, we study the interaction between the cloud/fog providers and the miners in a proof of work-based blockchain network using a game theoretic approach. In particular, we propose a lightweight infrastructure of the proof of work-based blockchains, where the computation-intensive part of the consensus process is offloaded to the cloud/fog. We formulate the computation resource management in the blockchain consensus process as a two-stage Stackelberg game, where the profit of the cloud/fog provider and the utilities of the individual miners are jointly optimized. In the first stage of the game, the cloud/fog provider sets the price of offered computing resource. In the second stage, the miners decide on the amount of service to purchase accordingly. We apply backward induction to analyze the sub-game perfect equilibria in each stage for both uniform and discriminatory pricing schemes. For uniform pricing where the same price applies to all miners, the uniqueness of the Stackelberg equilibrium is validated by identifying the best response strategies of the miners. For discriminatory pricing where the different prices are applied, the uniqueness of the Stackelberg equilibrium is proved by capitalizing on the variational inequality theory. Further, the real experimental results are employed to justify our proposed model.Item Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey(IEEE Communications Surveys & Tutorials, 6/21/2016) Luong, Nguyen Cong; Hoang, Ding Thai; Wang, Ping; Niyato, Dusit; Kim, Dong In; Han, ZhuThis paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless sensor networks (WSNs) are the main components of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in machine-to-machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.Item Deferrable load scheduling under imperfect data communication channel(Wireless Communications and Mobile Computing, 3/10/2014) Dong, Qiumin; Niyato, Dusit; Wang, Ping; Han, ZhuIn smart grid, the real?time pricing is implemented to motivate power consumers to change their consumption profile dynamically. With the real?time pricing, a deferrable load can be scheduled by its scheduler optimally so that the power consumption cost will be minimized. However, when the data communication in smart grid suffers from interference, congestion, malfunction in devices, or even cyber attack, it is possible that the power price information cannot be transmitted successfully to the scheduler. As a result, the scheduling performance will be negatively affected by the suboptimal decision?making because of incomplete power price information. To overcome this problem, a partially observable Markov decision process based deferrable load scheduling algorithm is proposed. Besides, the implementation of a standby alternative channel with the purpose to improve the reliability of the data communication in smart grid is also discussed in this paper. The numerical results show that the proposed partially observable Markov decision process based algorithm and the implementation of standby channel can effectively improve the scheduling performance when the scheduler lacks actual price information.Item Privacy Management and Optimal Pricing in People-Centric Sensing(IEEE Journal on Selected Areas in Communications, 3/15/2017) Alsheikh, Mohammad Abu; Niyato, Dusit; Leong, Derek; Wang, Ping; Han, ZhuWith the emerging sensing technologies, such as mobile crowdsensing and Internet of Things, people-centric data can be efficiently collected and used for analytics and optimization purposes. These data are typically required to develop and render people-centric services. In this paper, we address the privacy implication, optimal pricing, and bundling of people-centric services. We first define the inverse correlation between the service quality and privacy level from data analytics perspectives. We then present the profit maximization models of selling standalone, complementary, and substitute services. Specifically, the closed-form solutions of the optimal privacy level and subscription fee are derived to maximize the gross profit of service providers. For interrelated people-centric services, we show that cooperation by service bundling of complementary services is profitable compared with the separate sales but detrimental for substitutes. We also show that the market value of a service bundle is correlated with the degree of contingency between the interrelated services. Finally, we incorporate the profit sharing models from game theory for dividing the bundling profit among the cooperative service providers.Item Resource Management in Cloud Networking Using Economic Analysis and Pricing Models: A Survey(IEEE Communications Surveys & Tutorials, 1/5/2017) Luong, Nguyen Cong; Wang, Ping; Niyato, Dusit; Wen, Yonggang; Han, ZhuThis paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g., resource allocation, bandwidth reservation, request allocation, and workload allocation. Economic and pricing models have received a lot of attention as they can lead to desirable performance in terms of social welfare, fairness, truthfulness, profit, user satisfaction, and resource utilization. This paper reviews applications of the economic and pricing models to develop adaptive algorithms and protocols for resource management in cloud networking. Besides, we survey a variety of incentive mechanisms using the pricing strategies in sharing resources in edge computing. In addition, we consider using pricing models in cloud-based software defined wireless networking. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to cloud networking.Item Smart data pricing models for the internet of things: a bundling strategy approach(IEEE Network, 3/21/2016) Niyato, Dusit; Hoang, Dinh Thai; Luong, Nguyen Cong; Wang, Ping; Kim, Dong In; Han, ZhuThe Internet of Things (IoT) has emerged as a new paradigm for the future Internet. In IoT, devices are connected to the Internet and thus are a huge data source for numerous applications. In this article, we focus on addressing data management in IoT through using a smart data pricing (SDP) approach. With SDP, data can be managed flexibly and efficiently through intelligent and adaptive incentive mechanisms. Moreover, data is a major source of revenue for providers and partners. We propose a new pricing scheme for IoT service providers to determine the sensing data buying price and IoT service subscription fee offered to sensor owners and service users, respectively. Additionally, we adopt the bundling strategy that allows multiple providers to form a coalition and offer their services as a bundle, attracting more users and achieving higher revenue. Finally, we outline some important open research issues for SDP and IoT.Item The Accuracy-Privacy Trade-off of Mobile Crowdsensing(IEEE Communications Magazine, 6/13/2017) Alsheikh, Mohammad Abu; Jiao, Yutao; Niyato, Dusit; Wang, Ping; Leong, Derek; Han, ZhuMobile crowdsensing has emerged as an efficient sensing paradigm that combines the crowd intelligence and the sensing power of mobile devices, such as mobile phones and Internet of Things gadgets. This article addresses the contradicting incentives of privacy preservation by crowdsensing users, and accuracy maximization and collection of true data by service providers. We first define the individual contributions of crowdsensing users based on the accuracy in data analytics achieved by the service provider from buying their data. We then propose a truthful mechanism for achieving high service accuracy while protecting privacy based on user preferences. The users are incentivized to provide true data by being paid based on their individual contribution to the overall service accuracy. Moreover, we propose a coalition strategy that allows users to cooperate in providing their data under one identity, increasing their anonymity privacy protection, and sharing the resulting payoff. Finally, we outline important open research directions in mobile and people- centric crowdsensing.Item When Mobile Blockchain Meets Edge Computing: Challenges and Applications(IEEE Communications Magazine, 8/14/2018) Xiong, Zehui; Zhang, Yang; Niyato, Dusit; Wang, Ping; Han, ZhuBlockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized data management framework. Although blockchain has been widely adopted in many applications (e.g., finance, healthcare, and logistics), its application in mobile services is still limited. This is due to the fact that blockchain users need to solve preset proof-of-work puzzles to add new data (i.e., a block) to the blockchain. Solving the proof of work, however, consumes substantial resources in terms of CPU time and energy, which is not suitable for resource-limited mobile devices. To facilitate blockchain applications in future mobile Internet of Things systems, multiple access mobile edge computing appears to be an auspicious solution to solve the proof-of-work puzzles for mobile users. We first introduce a novel concept of edge computing for mobile blockchain. Then we introduce an economic approach for edge computing resource management. Moreover, a prototype of mobile edge computing enabled blockchain systems is presented with experimental results to justify the proposed concept.Item Wireless charger networking for mobile devices: fundamentals, standards, and applications(IEEE Wireless Communications, 4/29/2015) Lu, Xiao; Niyato, Dusit; Wang, Ping; Kim, Dong In; Han, ZhuWireless charging is a technique of transmitting power through an air gap to an electrical device for the purpose of energy replenishment. Recently, wireless charging technology has significantly advanced in terms of efficiency and functionality. This article first presents an overview and fundamentals of wireless charging. We then provide the review of standards, that is, Qi and the Alliance for Wireless Power, and highlight their communication protocols. Next, we propose a novel concept of wireless charger networking that allows chargers to be connected to facilitate information collection and control. We demonstrate the application of the wireless charger network in user-charger assignment, which clearly shows the benefit in terms of reduced costs for users to identify the best chargers to replenish energy for their mobile devices.Item Wireless Networks With RF Energy Harvesting: A Contemporary Survey(IEEE Communications Surveys & Tutorials, 11/10/2014) Lu, Xiao; Wang, Ping; Niyato, Dusit; Kim, Dong In; Han, ZhuRadio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next-generation wireless networks. As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service requirements. In this paper, we present a comprehensive literature review on the research progresses in wireless networks with RF energy harvesting capability, which is referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications. Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations and review the communication protocols specially designed for RF-EHNs. We also explore various key design issues in the development of RF-EHNs according to the network types, i.e., single-hop networks, multiantenna networks, relay networks, and cognitive radio networks. Finally, we envision some open research directions.